A global positioning system (GPS) has been generally known as a technology for identifying the location of a mobile object. The GPS allows an in-vehicle receiver to receive radio waves transmitted from GPS satellites and perform positioning on the basis of clock-time differences from the transmissions of the radio waves until the receptions of the radio waves.
In positioning systems based on radio technologies, such as the GPS, there has been a problem that it is difficult to perform positioning at spots where at least predetermined number of radio waves cannot be received. As specific examples, valleys between buildings and undergrounds are given, and, in urban areas, a situation in which positioning is unavailable sometimes occurs.
As technologies each enabling prevention of the occurrence of such a problem, and having a principle completely different from that of the GPS, there have been disclosed technologies each for identifying a current location of a mobile object by collating scenery images acquired by a camera mounted on the mobile object with a database related to scenery images having been stored in advance.
In Patent document 1, there is a positioning method described below. That is, this positioning method is such that shape data representing the planar shapes of roads, and information related to the heights and colors of surrounding buildings are extracted from scenery images acquired by a camera mounted on a mobile object, and a current location of the mobile object is identified by collating the above data and information with an already built database.
In Patent document 2, there is disclosed a positioning method in which the locations of feature points regarding road indications are extracted from scenery images acquired by a camera mounted on a mobile object, and a current location of the mobile object is identified by collating the above with an already built database.
In Patent document 3, there is disclosed a positioning method in which, targeting a mobile object operating under the indoor environment, a ceiling is photographed with a camera mounted on a mobile object, and a current location and posture of the mobile object is identified by collating an image resulting from the photograph with an already built database.
Further, as a technology, not used for the purpose of positioning, in which, just like in the technology disclosed in patent literature 2, collating with a database is performed on the basis of feature points extracted from scenery images, such a method for detecting obstacles as described below are disclosed in non-patent literature 1. That is, in this method, scenery images acquired by a camera mounted on a mobile object are correlated with an already built database with respect to feature points which are called SIFT. Further, obstacles are detected by calculating differences between road-surface area images which have been determined to be correlated with each other. Here, the SIFT is an abbreviation of scale-invariant feature transform. In this method, as a mechanism for making it possible to properly correlate the scenery images and the already built database even when erroneously correlated feature points are mixed, a trial-and-error parameter estimation method, which is called a random sample consensus (RANSAC), is employed.
In Patent document 4, there is disclosed a variation area recognition apparatus described below which is based on a scenery image acquired by a camera mounted on a mobile object. In this apparatus, through correlation of the acquired scenery image with an already built database, an alignment thereof is performed, and areas each resulting in a discrepancy after the alignment are extracted as variation areas, that is, areas in which objects, which did not exist when the database was created, exist.